• Acta Optica Sinica
  • Vol. 44, Issue 24, 2400001 (2024)
Zhonghui Tan1, Shuo Ma1,*, Chao Liu2,3,**, Weihua Ai1..., Tingting Ye1, Xianbin Zhao1, Shensen Hu1, Bo Li3, Miao Zhang3 and Wei Yan1|Show fewer author(s)
Author Affiliations
  • 1College of Meteorology and Oceanography, National University of Defense Technology, Changsha 410073, Hunan , China
  • 2Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/China Meteorological Administration Aerosol-Cloud-Precipitation Key Laboratory, School of Atmospheric Physics, Nanjing University of Information Science & Technology, Nanjing 210044, Jiangsu , China
  • 3Innovation Center for Fengyun Meteorological Satellite (FYSIC), National Satellite Meteorological Center (National Center for Space Weather), Beijing 100081, China
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    DOI: 10.3788/AOS241024 Cite this Article Set citation alerts
    Zhonghui Tan, Shuo Ma, Chao Liu, Weihua Ai, Tingting Ye, Xianbin Zhao, Shensen Hu, Bo Li, Miao Zhang, Wei Yan. Research Progress in Cloud Base Height Retrieval Algorithms Based on Satellite Multi-Spectral Radiometer Imagers[J]. Acta Optica Sinica, 2024, 44(24): 2400001 Copy Citation Text show less
    Diagram of satellite observing visible and infrared radiation from clouds
    Fig. 1. Diagram of satellite observing visible and infrared radiation from clouds
    Single signal degrees of freedom (DOF) for cloud top height and cloud base height in given atmospheric conditions. (a) Cloud top height; (b) cloud base height
    Fig. 2. Single signal degrees of freedom (DOF) for cloud top height and cloud base height in given atmospheric conditions. (a) Cloud top height; (b) cloud base height
    Distributions of cloud water content (CWC) in different seasons, latitudes, and surface types, derived from active CPR-CALIOP measurements
    Fig. 3. Distributions of cloud water content (CWC) in different seasons, latitudes, and surface types, derived from active CPR-CALIOP measurements
    CBH retrievals derived from FY-4B/AGRI on August 31, 2023 at 03:00 UTC
    Fig. 4. CBH retrievals derived from FY-4B/AGRI on August 31, 2023 at 03:00 UTC
    Comparison between CPR-CALIOP data and CBH retrievals for multi-layer clouds using MODIS, derived from (a) a single-layer cloud assumption-based method; (b) an extrapolation method based on cloud continuity
    Fig. 5. Comparison between CPR-CALIOP data and CBH retrievals for multi-layer clouds using MODIS, derived from (a) a single-layer cloud assumption-based method; (b) an extrapolation method based on cloud continuity
    MethodAdvantageLimitation
    Extrapolation

    • Based on cloud continuity

    • Directly derived from active measurements

    • Limited application scenarios

    • Highly affected by extrapolation distance

    Semi-empirical estimate

    • Independent retrieval from passive radiometers

    • Physical Interpretability

    • Rely on assumption on cloud micro-physics

    • Spatiotemporal variation of clouds affects validity of empirical coefficients

    Machine learning model

    • Powerful nonlinear fitting capability

    • Inclusion of multiple variables

    • Poor physical interpretability

    • Stability needs to be examined

    Hand of multi-layer clouds• Simultaneous retrieval of both cloud layers• Affected by multi-layer cloud detection accuracy
    Table 1. Main advantages and limitations of existing CBH retrieval methods
    Zhonghui Tan, Shuo Ma, Chao Liu, Weihua Ai, Tingting Ye, Xianbin Zhao, Shensen Hu, Bo Li, Miao Zhang, Wei Yan. Research Progress in Cloud Base Height Retrieval Algorithms Based on Satellite Multi-Spectral Radiometer Imagers[J]. Acta Optica Sinica, 2024, 44(24): 2400001
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